Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Written by
Benny Yazdanpanahi
Chief Information Officer, City of Tyler
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09
May 2021
Insights from City of Tyler CIO Benny Yazdanpanahi, who keeps several Texas cities safe in the rapidly evolving and unpredictable threat landscape of today’s world.
The City of Tyler is the largest city in Northwest Texas, with a population of more than 100,000, and home to several major financial, health, and educational institutions. As such, it is an attractive target for cyber-criminals.
Although we were not a full SolarWinds customer, the recent breach illuminated the fundamental flaws in a rules and signatures based security approach. Cyber security must be adaptive for you to mitigate ever-present risk. As IT professionals, I believe we have a responsibility to educate business leaders – and ultimately the SolarWinds attack should serve a wakeup call to all organizations, no matter what providers they use, to reevaluate and strategize security beyond signature-based tooling. Cities must protect constituents from threats that are impossible to predict, often on small budgets and with lean teams. Here is how we do it.
Cyber AI as the key layer to an organization’s security
In order to protect your organization, you have to understand your entire digital enterprise. You have to understand what is happening within your infrastructure. If someone is uploading videos all the time and that is normal, my security technology needs to understand that. Robust security must know that if something comes from a certain resource, in a certain way, then it is okay in that context. But if these parameters subtly shift, it might be an indicator of an active threat. This is where Cyber AI becomes critical – it looks at human and enterprise behavior, and learns and grows with the organization. When something is anomalous, it does that threat investigation and response automatically. And importantly – it’s not black and white.
We originally turned to AI because heuristic tools were limiting. Most security vulnerability comes from people’s behaviors. Although we train our staff about phishing and other vulnerabilities, having an intelligent security solution is necessary. AI has become popular, but Darktrace Cyber AI truly self-learns all the subtleties of our evolving digital infrastructure.
In our Proof of Value with Darktrace Cyber AI, it actually showed us information we didn’t see before with our existing tools, and this proved to be information that was critical to monitor to stay ahead of unseen threats. Armed with Darktrace, we now know what is happening across all our environments, down to if a new device is on the network that isn’t a part of our IT. If anything is deemed a significant deviation from the normal, it is flagged immediately. This is the power of Darktrace’s machine learning. It learns the DNA of your organization and allows you to see what is most pertinent. This is a crucial and necessary ability for every organization. You can buy all kinds of products, but you must understand your network to know which threats you need to pay most attention to.
Being proactive: Fighting threats with AI
At the City of Tyler, we believe that security is layered. It is not enough to just have a firewall. You have to be proactive and have multiple layers. You have to do the basics, like patching software and educating the workforce – but all of this is just one layer of security. What Darktrace does which makes it stand out from the pack, is that it gives us the ability to react and fight back with Autonomous Response. This is critical when working to mitigate risk.
Antigena Email scrubs our email, seamlessly complementing our existing tools and strategy. The AI actually looks at the way people write emails and knows if their style is different. Antigena Email learns the human behind the accounts on City of Tyler’s infrastructure, using Darktrace’s Cyber AI to learn a unique sense of ‘self’ for the city’s email communications. By understanding what is ‘normal’ for every internal user, external sender, and all the complex relationships between them, Antigena Email neutralizes threats before they even reach the city’s users. It is the only tool that intelligently actions threats in the inbox in this way.
Antigena Network provides this proactive protection to the entire infrastructure, no matter the environment. As our employees moved to remote working, understanding what is normal across contexts has been imperative to our cyber strategy. We have a 24-hour staff rotation and I like to be a hands-on CIO, but Antigena, a solution that actually acts on all the information we have, is crucial in securing our city day in and day out. It is our on-going goal to be proactive about threats – Antigena drives this forward.
Stronger security with collaboration
Municipalities generally don’t have large budgets for cyber security, and small cities may have the purchasing power to buy only a few products. With AI achieving so much in one solution, an organization can do a lot with a single technology, as opposed to piling on tools meant to mitigate particular known risks.
We work with other cities, and share our best practices, because we don’t operate on an island by ourselves. We live in a community, and IT is often the catalyst for collaboration. Other smaller cities might not have as many resources, but sharing our use cases and what we think works can help our sister cities. This community collaboration is how we can help. It makes everyone safer.
We are uniquely fortunate in that before the pandemic even happened, most of our staff were already educated on how to use remote working tools. We were always thinking about how we could make the office seamless, but in today’s world, it is becoming imperative to embrace dynamic collaboration. Many organizations are rapidly innovating to be effective whilst remote, and it has opened up a lot of new vulnerabilities very quickly. Cyber AI is perfectly positioned to support this given it is fundamentally adaptable. From virtual deployment to expert SOC handling from a mobile app, Cyber AI is the solution to secure major infrastructure shifts. With the Darktrace Mobile App, I have been able to monitor and protect the organization from anywhere and see what I need to see at the touch of a button.
I have been here for 19 years educating city leaders about new technologies. I believe cyber security resilience comes from three points: people, process, and technology. AI allows these three to work together in combination. With full visibility, you can pinpoint vulnerabilities before they are breached, whether they originate from the people, the process, or the technology. With the ability to respond to threats autonomously, you have a built-in process layer to protect your infrastructure when it counts the most.
Darktrace cyber analysts are world-class experts in threat intelligence, threat hunting and incident response, and provide 24/7 SOC support to thousands of Darktrace customers around the globe. Inside the SOC is exclusively authored by these experts, providing analysis of cyber incidents and threat trends, based on real-world experience in the field.
Hola VPN Abuse: From Proxy Traffic to Malware and Cryptomining
Introduction
In enterprise environments, non-compliant software traffic can introduce unexpected exposure by creating unmanaged paths for outbound connectivity. Hola VPN is a notable example because of its peer-to-peer design, which can effectively turn user devices into routing or exit nodes for other parties’ traffic, shifting the risk profile from that of a traditional virtual private network (VPN) to something closer to a distributed proxy.
As a result, the appearance of Hola-related activity, whether from prior installation or unintended background connections, should be treated with caution. Such activity may provide a foothold for malicious behavior, including lateral movement or command-and-control communication.
This blog explores how Hola-associated activity appeared as part of broader patterns of suspicious behavior observed across the Darktrace customer base.
The campaign
In February and March 2026, Darktrace observed similar anomalous activity across multiple customer environments, with affected devices showing consistent behavioral patterns. These included connections to multiple *.hola[.]org endpoints using Hola-related user agents, suggesting interaction with Hola infrastructure rather than isolated or incidental traffic.
Following these connections, affected customer environments showed downloads of suspicious executable files from rare external endpoints 188.241.219[.]55 and 184.241.218[.]111. Both endpoints have been flagged as potentially malicious by open-source intelligence (OSINT) [1][2].
These downloads were conducted using consistent user agents across impacted customers, specifically ‘Hola svc_js_win32/1.249.408’ and ‘Hola svc_js_win32/1.251.389’, suggesting a possible association with Hola-related activity.
Notably, this pattern aligns with recent reporting that, in some cases, Hola distributed an undeclared executable component, me[.]exe, which was later assessed to be a likely Monero-mining binary introduced via a compromised delivery pipeline [3].
Case Study 1
Darktrace first observed a new device on January 19, 2026, within a customer environment based in the Europe, Middle East, and Africa (EMEA) region. On the same day it appeared on the network, the device communicated with multiple pieces of Hola VPN-linked infrastructure before downloading a binary from a hola[.]org subdomain.
Figure 1: Cyber AI Analyst investigation highlighting Hola VPN service activity potentially associated with subsequent HTTP command-and-control (C2) connections.
Subsequent Darktrace telemetry revealed a recurring pattern of activity from the day the device was first observed through to March 4, 2026. During this period, the device repeatedly issued HTTP GET requests to the URI /bwfile?size=1048576, each returning a 200 OK response, indicating successful file retrieval.
This behavior was accompanied by a POST request to /bwfile, followed by an additional GET request for a significantly larger file at /bwfile?size=26214400, suggesting a deliberate and structured file transfer pattern.
Notably, the binary download activity was not tied to a single static host. Instead, it was observed across multiple URLs that changed over time while remaining within the same hola[.]org domain. This pattern suggests the use of rotating or distributed delivery infrastructure rather than a fixed endpoint.
Figure 2: Variation in URLs over time within the same hola[.]org domain, indicating the use of dynamically changing endpoints.
Across these events, the activity was consistently associated with the user agent Hola svc_js_win32/1.249.408, further linking the traffic to Hola-related service components. Amid these persistent and unusual connections, on February 22, Darktrace observed the device connecting to 188.241.219[.]55/proxy-peer-windows-amd64[.]exe, resulting in the download of an executable file.
Figure 3: File transfer event showing the download of an executable from the rare external endpoint 188.241.219[.]55.
Based on its file hash, the downloaded file was assessed as a likely Trojan downloader [4], with import hash (imphash) values showing similarities to samples linked to Vidar, Rhadamanthys, and Stealc according to OSINT [5]. Overall, this sequence of activity suggests that Hola-related connectivity may have been leveraged as part of a broader malware delivery chain.
Darktrace’s Autonomous Response
Due to the highly unusual activity observed, Darktrace Autonomous Response was triggered by the device’s behavior. However, as the customer deployment was configured in “Human Confirmation” mode, manual approval was required before any action could be taken.
Had the deployment been set to “Fully Autonomous” mode, Darktrace would have automatically:
Blocked connections to the associated ports and external endpoints
Prevented all outgoing network connections from the device
Enforced the device’s established ‘pattern of life’, allowing normal activity to continue while restricting any anomalous behavior
Figure 4: Example of a Darktrace Autonomous Response model highlighting the action that would have been taken, demonstrating how the system identifies anomalous behavior and applies targeted containment measures to restrict suspicious network activity.
Case Study 2
While the first case focused on anomalous activity from a newly observed device, Darktrace also identified cases in which devices had already been communicating with Hola-related endpoints prior to the suspected campaign. This may suggest pre-existing Hola usage within the environment, potentially increasing exposure and creating an avenue for subsequent suspicious activity.
One case involved three devices within a customer network based in the Americas (AMS). In this instance, a different payload was identified: me[.]exe, a potentially malicious cryptocurrency miner also referred to as HolaMonitorService[.]exe [6][7]. The downloads were observed from infrastructure similar to that seen in Case 1, including an IP address within the same 188.241.0.0/16 subnet.
Connections to *.hola[.]org, alongside the use of potential Hola-related user agents consistent with those in Case 1, were also identified, further suggesting a link between the observed activity and Hola-associated infrastructure.
Darktrace observed activity indicative of unusual VPN usage on the first affected device on February 2, followed by telemetry suggesting potential Tor usage. This was later followed by the download of me[.]exe on March 10 from 188.241.218[.]111. Notably, this device was the earliest among the three within the deployment to exhibit the presence of the suspicious executable.
Figure 5: Cyber AI Analyst detection highlighting the download of a suspicious executable from a similar external endpoint in a separate deployment.
On March 5, 2026, the second affected device exhibited a slightly different progression, initiating connections to http-test1[.]hola[.]org using the user agent ‘hola_get’. This activity was followed by the download of me[.]exe from the same endpoint on March 13, consistent with the broader pattern of Hola-related downloads observed across the environment.
Figure 6: Example of Hola VPN-related connectivity observed on the network prior to the suspected campaign, indicating pre-existing usage that may have contributed to subsequent activity.
The final affected device within this customer’s network demonstrated a more limited but related pattern, also downloading me[.]exe on March 17 using the same ‘hola_get’ user agent.
While the earlier Hola VPN usage observed across the deployment may not have been directly related to the suspected malware campaign, it may nonetheless have contributed to reduced visibility. The presence of pre-existing Hola-related traffic could have obscured malicious activity, making it more difficult to distinguish legitimate usage from attacker-driven behavior and, in turn, hindering the timely identification of the emerging compromise.
Darktrace’s Autonomous Response
For this deployment, the customer had their Autonomous Response capability configured in “Fully Autonomous” mode, allowing Darktrace to take action without human intervention. As a result, the system was able to autonomously disrupt the activity as soon as relevant events were identified through model detections.
Figure 7: Darktrace Autonomous Response actions taken against suspicious activity linked to Hola VPN.
Suspected cryptomining activity
As previously noted, some of the observed executable payloads appear to be linked to cryptomining malware. Across a subset of affected customer environments, this assessment was further supported by subsequent device activity consistent with Monero mining. Affected devices established follow-on connections to multiple external endpoints aligned with known mining infrastructure, indicating post-download execution.
Considering the broader sequence of activity, this pattern may point to a wider form of abuse in which legitimate VPN-related traffic is used to mask or facilitate malicious behavior following compromise.
On several devices, the download of executable files, including a newly observed peer[.]exe, was followed by alerts indicative of cryptocurrency mining activity. Mining-related credentials such as ‘x’ were observed using the Minergate protocol to communicate with endpoints within the 89.125.255.0/24 subnet and 188.241.218[.]111, the same endpoint involved in earlier download activity. Additional credentials appeared to reflect device-specific CPU identifiers, for example ‘12th Gen Intel(R) Core (TM) i5-1235U’.
Observed mining methods included login, submit, and job, consistent with active participation in a pool-based mining workflow rather than passive or incidental contact. The login method indicates that the host authenticated to the mining service as a worker, job reflects the assignment of computational tasks, and submit shows completed work being returned to the pool [8]. This sequence suggests that affected devices were actively contributing processing resources as part of an unauthorized distributed mining operation.
The presence of unauthorized cryptominers can lead to degraded system performance and reduced device stability. Beyond the immediate resource impact, such activity often serves as an indicator of a broader compromise rather than an isolated issue. This may increase the risk of further malware deployment, persistence mechanisms, and lateral movement, particularly in environments where the initial intrusion has not been fully contained.
Conclusion
Across affected environments, detections such as unusual VPN usage, connections to Hola infrastructure, anomalous HTTP activity, suspicious file downloads, and subsequent cryptomining behavior were linked into a single, evolving incident narrative. This aggregation provided a clearer view of attack progression, enabling security teams to understand not just isolated alerts, but the full sequence of compromise from initial contact through to post-exploitation.
Ultimately, these activities show that the risk posed by non-compliant software such as Hola VPN can extend far beyond simple policy violations. What began as traffic to Hola-related infrastructure was, in multiple cases, followed by behavior suggesting deliberate misuse, including suspicious executable downloads using Hola-related user agents and, in some instances, evidence of active cryptomining. These were not isolated anomalies, but elements of a broader pattern in which seemingly benign proxy or VPN-related communications may have created a pathway for malicious delivery and unauthorized resource exploitation.
The significance of this activity lies not only in the downloads or mining, but in what it reveals about an attacker’s ability to blend malicious operations into traffic associated with software that may already have a foothold in the environment. When unapproved software operates within an enterprise, it can reduce visibility, blur the distinction between legitimate and malicious traffic, and create opportunities to extend compromise in ways that are persistent and difficult to detect. Darktrace’s anomaly-based approach enables these behavioral distinctions to be identified, regardless of whether the device is new or long established within the network.
Credit to Min Kim (Associate Principal Analyst), Priya Thapa (Senior Cyber Analyst) Edited by Ryan Traill (Content Manager)
![Variation in URLs over time within the same hola[.]org domain, indicating the use of dynamically changing endpoints.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/6a304bdeff111215c0436931_Screenshot%202026-06-15%20at%2012.00.43%E2%80%AFPM.png)
![File transfer event showing the download of an executable from the rare external endpoint 188.241.219[.]55.](https://cdn.prod.website-files.com/626ff4d25aca2edf4325ff97/6a304c2468d20aeff16a2721_Screenshot%202026-06-15%20at%2012.01.53%E2%80%AFPM.png)
